This paper develops a weakly supervised algorithm that learns to segment rigid multi-colored objects from a set of training images and key points. The approach uses congealing to ...
Douglas Moore, John Stevens, Scott Lundberg, Bruce...
This paper presents a novel approach to robust and flexible person tracking using an algorithm that combines two powerful stochastic modeling techniques: The first one is the tech...
We propose a new method for handwritten word-spotting which does not require prior training or gathering examples for querying. More precisely, a model is trained "on the fly...
In this paper we apply state-of-the-art approach to object detection and localisation by incorporating local descriptors and their spatial configuration into a generative probabil...
Joni-Kristian Kamarainen, Miroslav Hamouz, Josef K...
In this paper, we demonstrate that multiscale Bayesian image segmentation can be enhanced by improving both contextual modeling and statistical texture characterization. Firstly, ...